Ask Quebit About Analytics

Episode 22: A Practical Approach to Innovation in Analytics Guest: Andreas Kugelmeier, IBM Innovation is much easier to talk about than to do in practice. Challenges include getting buy-in from groups you depend on but have little leverage over, and resisting the urge to go for a BIG vision. In this episode, Andreas Kugelmeier from the IBM Data and AI Labs, talks about the concept of a Business Analytics Innovation Loop as a practical, low-risk and high-reward approach to effecting innovation. The concept has strong parallels with the notion of agile software development, in which progress is made through a sequence of incremental but valuable steps. In Business Analytics there is an added advantage to taking an incremental approach because each steps brings new insights and understanding to light, which can inform and change subsequent steps for the better! Andreas uses an extensive example from Financial Planning and Analysis (FP&A) in banking to illustrate his point, and makes an important point about

Episode 21: Everything you always wanted to know about Testing Guest: Jim Brinnen When implementing a new analytics system, testing is sometimes treated as a “nice-to-have” rather than a core requirement. While no one says up-front that testing is a low priority, it is not unusual for there to be inadequate dollars, time and planning set aside for testing. While this is true for any software application implementation, it may be particularly true in analytics because analytics projects are often initiated and owned by the Line of Business, rather than IT. This is a good thing because the Business recognizes business value when it sees it (and can thus be a very engaged partner), but issues may arise because the Business typically has limited experience in implementing software systems. At the beginning of the project, the challenges of acquiring data and defining requirements can be overwhelming. It is normal to go through a process of learning that leads to changed expectations and modified scope. Since anal

Episode 20: Data Virtualization Guest: Keith Hollen Data Virtualization technologies can be used in a number of different ways, including real-time operational reporting and analytics against multiple source systems, and quick-and-dirty data exploration! As business users increasingly expect to have direct access to data for self-service analytics, data virtualization can be an effective way to make that possible. In this episode, QueBIT Data Expert Keith Hollen explains what data virtualization is, and how it fits into the pantheon of data management tools and strategies. While not a replacement for a true data warehouse, it can be a viable alternative to an Operational Data Store to enable analytics and reporting. Keith ends with Good and Bad Use Case examples to help explain when data virtualization may be valuable, and when it likely will not be.

Episode 19: Lean Demand Forecasting Guest: Dan Barrett Dan Barrett, QueBIT’s Advanced Analytics Technical Sales Manager, claims that MOST companies waste far too much time on demand forecasting! Considering how crucial an accurate demand forecast is to planning your supply chain, this is a bold statement. Keep in mind that Dan is NOT saying that you don’t need a demand forecast: of course you do! The problem he wants to address is accuracy, and his point is that more people spending more time on it does not typically result in a commensurate increase in accuracy. In this episode, Dan explains what he means by Lean Demand Forecasting, and how measuring a metric called Forecast Value Add that compares your forecast to actuals on a continuous basis is an important tool for real forecast accuracy improvement. We compare different approaches to demand forecasting, including when a naïve approach is good enough, and when building a predictive model becomes valuable.

Episode 18: The Evolution of Business Intelligence Guest: Robin Wilkinson It turns out that Business Intelligence (BI), as a concept, has been around since 1865! Back then it was a manual paper and pencil process, but it still enabled one business to prevail over its competitors by making better data driven decisions. Today we are dealing with massive amounts of data, technology has evolved tremendously, and people have evolved too! In this episode Robin Wilkinson, who is the General Manager of QueBIT’s Business Intelligence and Data Management practice, gives us a BI history lesson and takes us through how the process of implementing and deploying BI has evolved though the years. The conversation includes some great specific examples, and lots of great best practice advice for BI success. Among many other things, Robin points out that today everyone wants results quickly, so the focus needs to be one delivering BI solutions in days or weeks, not months or years.

Episode 18: Analytics for Retail Buyers Guest: Jim Hanifin As on-line shopping becomes the norm, the traditional retail industry is going through a lot of adjustments. Employing analytics technology to increase operational efficiency and make better decisions faster is an obvious avenue to take. In this episode we speak with Jim Hanifin who recounts the journey at a retail customer he worked with recently. We go into detail about how their retail buyers transitioned from a weekly paper-based analysis and planning system, to an on-line dashboard that put the data at their fingertips in real time. If you have ever wondered how retailers get the products you want to buy into stores, you should find this peek under the covers interesting! This episode is brought to you by QueBIT.

Episode 16: How to become an Analytics Expert Guests: Daniel Williams, Odile Davis Wolfe, Pete Horgan QueBIT has grown by cross-training business and finance people in analytics technology, and by cross-training engineers and computer scientists in business and finance. Meanwhile analytics experts such as data scientists are at a premium in the marketplace, and many finance and business leaders are recognizing the need for their business and financial analysts to develop more technical skills, so as to be able to service growing demands for data and insights in support of better decision making! Specifically, there is a trend towards the finance function expanding beyond responsibility for financial reporting, financial planning and analysis into a new world that encompasses data and analytics strategy for the entire organization! In this week’s episode, we put these two things together: perhaps QueBIT’s experience in developing these skill sets will be of use to organizations that are moving in this directio

Episode 15: A Financial Consolidation is an Analytics project! Financial Analytics is an important branch of the field of Analytics. It involves data management, modeling and reporting. A Financial Consolidation system is a Financial Analytics project that brings together data from one or more ERP (Enterprise Resource Planning) system together with a financial model with the purpose of producing consolidated financial reports. Not only are these obligatory for regulatory reporting, but they can also be a strategic asset. Shorter month-end closing cycles, coupled with detailed product/segment/regional/entity/etc reporting made available quickly, to front line managers WITH the ability to drill down for more detail in an intuitive and interactive manner … can all translate into business value. In this episode we tell the story of how a real QueBIT customer moved beyond Excel spreadsheets and implemented a robust enterprise financial consolidation system using a combination of a relational data art and a special

Episode 14: Nerding out on FP&A! Guest: Beth Thomas The Financial Planning & Analysis (FP&A) function is the original analytics function within any organization. The Profit & Loss (P&L), Balance Sheet and other financial statements tell the story of the business. When they are correct, timely, and reach the right audience, they are invaluable for identifying problems and driving informed decision-making. This week, Beth Thomas who is the General Manager of QueBIT’s Financial and Operational Performance Management business, and a former Manager of FP&A herself, shares her insights and experiences. She talks about why she finds FP&A so interesting, and how it is time to transcend Excel’s limitations by enhancing (NOT replacing) it with modern data management and modeling tools. Financial Analysts should be spending their time doing analysis and adding value to the business instead of being bogged down in mundane data collection and manipulation activities! The podcast ends with some

Episode 13: The Evolution of Analytics Solutions Guest: Gary Corrigan 15 years ago, when Gary Corrigan first sold analytics technologies, customers were looking for technology platforms. Today the landscape has changed, and customers are now looking for solutions to their specific business problems. That’s a significant change! It’s as though customers have gone from wanting to buy a truckload of bricks to shopping for ready-built houses – and Gary has had a front row seat! In this week’s podcast conversation, Gary articulates very clearly what the value of analytics technologies are to businesses, and how they are not a luxury add-on to an ERP (“Enterprise Resource Planning”) system, but an absolute necessity for any company to survive and thrive in today’s business environment. Among other things he talks about the importance of listening to and connecting with customer needs, and how it is just as important to figure out early that you are not a good fit, as it is to close a deal. At the end Gary shares va

Episode 12: My Bank FIRED me as their customer! A few years ago, A.G. – who lives in the United States - received a letter from her bank in Denmark telling her that their relationship would be terminated. A.G. still had several thousand dollars deposited in a checking account as well as an investment account. This personal story leads into a discussion of profitability modeling and allocations in general, and customer profitability modeling – especially in the context of financial institutions – specifically. Profitability models are a very interesting Analytics use case for several reasons. They are valuable as they can provide great insights into both problems and opportunities in a business. They are interesting to implement, as they require a combination of business understanding, creativity, data wrangling skills, technical smarts … and political finesse! In this episode we describe the value that profitability models can bring, and provide three valuable tips for how to be successful in deploying profit

Episode 11: Surprise! Analytics Isn’t About Changing Your Business! Guest: Joel Kehm Analytics is NOT about changing your business: it’s about running your business better! If your business is about manufacturing widgets to sell, your intention with analytics is probably not going to be to close down your factories and do something else. The value of analytics lies in improving the quality of what you do. It sounds obvious, but you can’t fix a problem that you don’t know exists, can you? Analytics is all about organizing your data, and presenting it back to you in a way that gives you information and insights. In this Episode we have a wide ranging and insightful discussion with QueBIT Principal Consultant Joel Kehm about the value of analytics, how to get started and what not to do. Along the way Doritos, parties and food recall solutions are used to add color to the discussion.

Episode 10: Implementing Predictive Demand Planning at a Paper Manufacturer Guest: Tim Corrigan Predictive Demand Planning is the classic application of Advanced Analytics. The idea is that historical actual data (how much of product X did you sell in region Y during time Z?), potentially combined with relevant external data (weather, demographics, economic indicators), can be used to forecast demand at a level of granular detail and accuracy beyond what can be done manually, using statistical techniques. In this episode, QueBIT’s Director of Strategy and Process Improvement Tim Corrigan recounts his experiences implementing a predictive demand planning solution at a large global paper manufacturer. The project was a case study in business process change and integrated financial planning, as well as typical Sales and Operations Planning (S&OP). Tim talks about some of the details they needed to figure out, how the data flowed through the process, and shares the key to their success.

 Episode 9: Using APIs to Customize your Analytics Solutions  Guest: Mike Cowie At QueBIT our purpose is to help companies make better decisions faster. Everything starts with data, which is used to understand the past, ACT in the present, and anticipate the future. Simple as that! For the most part, as consultants, we deliver analytics solutions using technology platforms created by other companies. But from time to time, that is not enough. In this week’s episode Mike Cowie, QueBIT’s Director of Strategic Solutions, explains what an API is, how they have evolved and gives us instructions on how to build a chat-bot! He then goes on to talk about how to find help when you start down the path of writing custom applications using APIs, and how there are penty of opportunities to give back. We end with a great discussion of community, and how community can be found in the most unexpected places.

Episode 8: Turning the Office of Finance into a Center for Data Analytics Guest: Cathy Jirak When Cathy Jirak and Gary Quirke founded QueBIT about 20 years ago, they were really just looking for a way to get their lives back! They enjoyed being consultants implementing financial planning, analysis and reporting solutions but found that there was a downside to success: 80 hour work weeks! In this episode Cathy talks about why QueBIT was founded and how they were able to grow the company without sacrificing quality. As businesses are under ever more pressure to be agile in a fast- moving world, the Office of Finance in any company needs to become better at measuring and monitoring performance and being reactive! Data are increasing in both speed and volume, and knowing how to use your data will separate the winners from the losers. This means that either financial analysts need to acquire data analysis and data science skills, or data scientists need to learn about finance and business. QueBIT has done both, an

Episode 7: Biotechnology Financial Modeling Case Study  Guest: Lance Antwine Lance Antwine, CPA and Implementation Manager at QueBIT, has had a long and successful career in finance and technology. In this episode Lance talks about a series of fascinating financial planning models he helped develop at a biotechnology firm. He describes how he worked with different groups to create a fully integrated financial model, starting with a fascinating research costing model (built up from the constituent molecules!), and flowing through to a strategic business plan and a full financial plan incorporating the income statement, balance sheet and cash flows – and more. Lance also talks about the business factors that contributed to the success of these projects, and how financial analysts and decision makers were able to automate their planning and data flows and win more time for high value analysis.

Episode 6: So you want to use Advanced Analytics to boost ROI? Here’s how.  Guest: Lee Allgood Before he came to QueBIT, Lee Allgood used to work at a large manufacturing company whose customers were retailers. In this episode, Lee talks about his experience implementing an advanced analytics solution at that company to optimize the placement of product samples at retail stores. Product samples were a large expense for this company, second only to salary expense. Optimizing the placement of samples both saved money and maximized revenue leading to greater ROI. The practical advice on how to make a project like this successful is just as fascinating as the business problem, and the analytics solution!

Guest: Leo Cohen  Leo Cohen began his professional career as a financial analyst in a very large corporation and has intimate first-hand knowledge of financial analytics including financial reporting, planning, forecasting and analysis. Today, as QueBIT’s NY Metro Sales Executive, he taps into those early experiences to empathize with his customers from the other side, and help them find ways to win back time to do better analyses. Besides telling some entertaining stories about his experiences in the analytics field, Leo finishes up by sharing solid, practical and valuable advice for any company in the market to buy a software solution. 

Guest: Jim Miller QueBIT Master Consultant Jim Miller has an unusual hobby: he researches and writes books about technology! Jim has written successful books on a variety of topics, but today we are going to talk about his series of books on IBM Watson, the most recent of which is called “Machine Learning with IBM Watson Studio”. In our conversation with Jim, we ask him to explain the various tools behind the IBM Watson brand, and then go on to talk about real-world business use-cases for Watson Studio. We wrap up by talking about how ANYONE can get started with the free version!

Guest: Dallas Crawford Predictive (and other Advanced) Analytics capabilities are often presented in a way that is daunting to the ordinary business person. Meanwhile the demand for people with data science skills is sky-rocketing, and there is anxiety about the opportunity cost of not leveraging these exciting new technologies. In this week’s conversation, we bring this seemingly abstract world down to earth, with a series of real-life examples that illustrate the value – and importance – of looking at these technologies. It turns out that once you focus on the business problem that you are trying to solve – which in QueBIT’s opinion is the only way to do analytics – a lot of the mystery disappears. We conclude by sharing what we have learned about how to make sure your data science efforts are successful.